相关论文: Breaking Political Filter Bubbles via Social Compa…
Social media have quickly become a prevalent channel to access information, spread ideas, and influence opinions. However, it has been suggested that social and algorithmic filtering may cause exposure to less diverse points of view, and…
We analyze online collective evaluation processes through positive and negative votes in various social media. We find two modes of collective evaluations that stem from the existence of filter bubbles. Above a threshold of collective…
Social media influence online activity by recommending to users content strongly correlated with what they have preferred in the past. In this way they constrain users within filter bubbles that strongly limit their exposure to new or…
Recent studies suggest that social media usage -- while linked to an increased diversity of information and perspectives for users -- has exacerbated user polarization on many issues. A popular theory for this phenomenon centers on the…
Polarization is a troubling phenomenon that can lead to societal divisions and hurt the democratic process. It is therefore important to develop methods to reduce it. We propose an algorithmic solution to the problem of reducing…
From a liberal perspective, pluralism and viewpoint diversity are seen as a necessary condition for a well-functioning democracy. Recently, there have been claims that viewpoint diversity is diminishing in online social networks, putting…
A filter bubble refers to the phenomenon where Internet customization effectively isolates individuals from diverse opinions or materials, resulting in their exposure to only a select set of content. This can lead to the reinforcement of…
People are shifting from traditional news sources to online news at an incredibly fast rate. However, the technology behind online news consumption promotes content that confirms the users' existing point of view. This phenomenon has led to…
Social media have great potential to support diverse information sharing, but there is widespread concern that platforms like Twitter do not result in communication between those who hold contradictory viewpoints. Because users can choose…
The suggestions generated by most existing recommender systems are known to suffer from a lack of diversity, and other issues like popularity bias. As a result, they have been observed to promote well-known "blockbuster" items, and to…
This work analyses surprising elections, and attempts to quantify the notion of surprise in elections. A voter is surprised if their estimate of the winner (assumed to be based on a combination of the preferences of their social connections…
The negative effects of misinformation filter bubbles in adaptive systems have been known to researchers for some time. Several studies investigated, most prominently on YouTube, how fast a user can get into a misinformation filter bubble…
News recommenders help users to find relevant online content and have the potential to fulfill a crucial role in a democratic society, directing the scarce attention of citizens towards the information that is most important to them.…
Online social media such as Twitter are widely used for mining public opinions and sentiments on various issues and topics. The sheer volume of the data generated and the eager adoption by the online-savvy public are helping to raise the…
In micro-blogging platforms, people connect and interact with others. However, due to cognitive biases, they tend to interact with like-minded people and read agreeable information only. Many efforts to make people connect with those who…
Social media platforms significantly influence ideological divisions by enabling users to select information that aligns with their beliefs and avoid opposing viewpoints. Analyzing approximately 47 million Facebook posts, this study…
Filter bubbles and echo chambers have received global attention from scholars, media organizations, and the general public. Filter bubbles have primarily been regarded as intrinsically negative, and many studies have sought to minimize…
Recommender systems, which offer personalized suggestions to users, power many of today's social media, e-commerce and entertainment. However, these systems have been known to intellectually isolate users from a variety of perspectives, or…
Recommender systems can be found everywhere today, shaping our everyday experience whenever we're consuming content, ordering food, buying groceries online, or even just reading the news. Let's imagine we're in the process of building a…
Our consumption of online information is mediated by filtering, ranking, and recommendation algorithms that introduce unintentional biases as they attempt to deliver relevant and engaging content. It has been suggested that our reliance on…